Product Invoice Recognition OCR Forms

Function Introduction

Wide Range of Recognizable Characters

The system supports multiple recognition engines such as printed Chinese characters, printed English, printed numbers, handwritten Chinese characters, handwritten English, handwritten numbers, magnetic codes, barcodes, customer signature detection, and attachment seal detection.

Bill Classification

Good at layout differentiation; accurately classify bills according to such features as inner frame line style, frame line color, title content, title color, text content, and text color

Preprocessing Function

Support such functions as automatic black edge removal, deviation correction, color cast correction, color filtering, noise reduction, binarization, enhanced recognition of unit contract, etc

Form Adaptation

Supports table recognition with frame lines and table recognition without frame lines. The system automatically detects and recognizes without manual intervention.

Provide Standard API

Support C++, C#, JAVA and other development language calls. Provide standard DLL to integrate with enterpise's ERP, CRM

Output Structural Data

Return JSON, XML recognition result

Multiple OCR Deployment Methods

Support privatized deployment at Windows and Linux servers

Multiple OCR Recognition Methods

Support OCR recognize black and white image and color image

Product Superiority

Template classification is accurate
The recognition rate of template classification is as high as 98%
High Recognition Rate
The recognition rate of printed Chinese characters is 99.5%. The recognition rate of printed English and numbers is higher than 99.6%
Fast OCR Recognition
Black and white bill image: 0.3~0.5s per sheet. Color bill image:0.3~1.0s per sheet
Provide Customization OCR Service
Quickly response to the development demands of various customized templates

Application Scenarios

  • Bank Supervision System
  • Insurance Company
  • Evaluation Industry
Bank Supervision System

The form bill recognition system is mainly used in the bank's post-surveillance system to help banks solve the identification and classification of bill images in the risk supervision system. Banks that have been traded include the four major banks of the ICBC, ABC,BCM, CCB ,Jinzhou Bank, Anhui Agricultural Credit, Hainan Bank, and Xinjiang Major banks such as Rural Credit Union.

Insurance Company

Staff input paper insurance policies into the insurance imaging system manually is slow,low accurate, and high in labor costs, which slows down the informatization development process of the insurance industry seriously. Our OCR tecnology can integrate with the insurance imaging system to achieve rapid input of insurance policy information so as to improve work efficiency and save labor costs, it has been successfully applied to insurance companies such as Sunshine Insurance, Taiping Insurance, and United Life Insurance.

Evaluation Industry

During various examinations or evaluations, OMR (cursor character recognition) products are used for information collection to identify various evaluation forms and questionnaires. This product has high requirements about printing paper quality and high cost of use. Many manufacturers are seeking lower costs and ensuring accuracy and high speed of the product, Our OCR recognition product helps various examinations and evaluations to input information quickly with high accuracy and low cost.

Case

License plate recognition camera applied to smart logistics park platform
Credential recognition improves telecom authentication efficiency
Wintone OCR empowers enterprise dealer system digitization